{"id":"W4410014583","doi":"10.1016/j.landig.2025.02.008","title":"Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study","year":2025,"lang":"en","type":"article","venue":"The Lancet Digital Health","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; School of Medicine, Shanghai Jiao Tong University; Economic and Social Research Council; Tongji Medical College, Huazhong University of Science and Technology; Natural Science Foundation for Young Scientists of Shanxi Province; National Science and Technology Major Project; Macau University of Science and Technology; Peking Union Medical College Hospital; Shanghai Jiao Tong University; Center for High Performance Computing, Shanghai Jiao Tong University; Office of the First Minister and Deputy First Minister; Ministry of Water Resources; Peking Union Medical College; Chinese University of Hong Kong; Huazhong University of Science and Technology; Queen's University; Health and Social Care Research and Development Division; Public Health Agency; United Kingdom Clinical Research Collaboration; Natural Science Foundation of Beijing Municipality; Centre for Ageing Research and Development in Ireland; National University of Singapore; Young Scientists Fund; Wolfson Foundation; Queen's University Belfast; Wellcome Trust; Shanghai Municipal Health Commission; Tongji University; National Natural Science Foundation of China; Chinese Academy of Medical Sciences; Innovative Research Team of High-level Local University in Shanghai","keywords":"Medicine; Retinal; Disease; Kidney disease; Population; Biopsy; Pathology; Radiology; Artificial intelligence; Computer science; Ophthalmology; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003682584,0.000170106,0.0006252706,0.0001846466,0.0001662963,0.00006028123,0.0001704899,0.00001922308,0.00001925835],"category_scores_gemma":[0.0006988732,0.0001208002,0.0001200898,0.0007223026,0.00004952725,0.00004758309,0.00005689108,0.0002130041,0.00002346837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009097665,"about_ca_system_score_gemma":0.0002831116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003597831,"about_ca_topic_score_gemma":0.00001236591,"domain_scores_codex":[0.9985534,0.00007034098,0.0003968597,0.0003126894,0.0003077044,0.0003589816],"domain_scores_gemma":[0.9985909,0.0003170095,0.0001661902,0.0004644672,0.00009521423,0.0003662565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003896527,0.0003949841,0.9878495,0.0005461731,0.00007402811,0.00001218631,0.0003214064,0.0003134222,0.00003558728,0.00001573129,0.0008004788,0.009246793],"study_design_scores_gemma":[0.001397866,0.0003601189,0.9947193,0.000794519,0.0002059493,9.994732e-7,0.0006711346,0.001211571,0.00014484,0.0002519181,0.0001100087,0.000131812],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806843,0.0001279792,0.001827655,0.01493019,0.00004142126,0.0008944779,0.00004349196,0.00008040006,0.001370087],"genre_scores_gemma":[0.995376,0.00001147743,0.0001962787,0.003793255,0.0001064891,0.0001274301,0.0001418719,0.000018364,0.0002288389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0146917,"threshold_uncertainty_score":0.4926088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01354851639341366,"score_gpt":0.3114841681117995,"score_spread":0.2979356517183859,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}